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Browse files- Benign 1.jpg +0 -0
- Benign 2.jpg +0 -0
- Benign 3.jpg +0 -0
- DS_Store +0 -0
- Malignant 1.jpg +0 -0
- Malignant 2.jpg +0 -0
- Malignant 3.jpg +0 -0
- README.md +5 -4
- app.ipynb +686 -0
- app.py +19 -0
- export.pkl +3 -0
- requirements.txt +2 -0
Benign 1.jpg
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Benign 2.jpg
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Benign 3.jpg
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DS_Store
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Binary file (6.15 kB). View file
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Malignant 1.jpg
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Malignant 2.jpg
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Malignant 3.jpg
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README.md
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---
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title:
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emoji:
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colorFrom: red
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colorTo:
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sdk: gradio
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sdk_version:
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app_file: app.py
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pinned: false
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---
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Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
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---
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title: Skin Cancer Detection
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emoji: 🐢
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colorFrom: red
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colorTo: blue
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sdk: gradio
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sdk_version: 3.32.0
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app_file: app.py
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pinned: false
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license: apache-2.0
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---
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Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
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app.ipynb
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{
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"cells": [
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"cell_type": "code",
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"execution_count": 1,
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"metadata": {},
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"outputs": [
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"output_type": "stream",
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"text": [
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"Defaulting to user installation because normal site-packages is not writeable\n",
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"Collecting fastai\n",
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" Using cached fastai-2.7.12-py3-none-any.whl (233 kB)\n",
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" Downloading matplotlib-3.7.1-cp39-cp39-macosx_10_12_x86_64.whl (7.4 MB)\n",
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"\u001b[K |████████████████████████████████| 7.4 MB 341 kB/s eta 0:00:01 |▏ | 51 kB 835 kB/s eta 0:00:09\n",
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"\u001b[?25hCollecting torchvision>=0.8.2\n",
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"\u001b[?25hCollecting scipy\n",
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"\u001b[?25hRequirement already satisfied: pip in /Library/Developer/CommandLineTools/Library/Frameworks/Python3.framework/Versions/3.9/lib/python3.9/site-packages (from fastai) (21.2.4)\n",
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{
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"ename": "FileNotFoundError",
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"evalue": "[Errno 2] No such file or directory: 'Benign1.jpg'",
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"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
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"\u001b[0;32m/var/folders/gm/h3z3dxv12z73tt5_q7j7kc6h0000gn/T/ipykernel_97601/3272737616.py\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mim\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mPILImage\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcreate\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'Benign1.jpg'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 2\u001b[0m \u001b[0mim\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mthumbnail\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m192\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m192\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
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"\u001b[0;32m/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/fastai/vision/core.py\u001b[0m in \u001b[0;36mcreate\u001b[0;34m(cls, fn, **kwargs)\u001b[0m\n\u001b[1;32m 123\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0misinstance\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfn\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mbytes\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mfn\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mio\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mBytesIO\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfn\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 124\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0misinstance\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfn\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mImage\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mImage\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mcls\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfn\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 125\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mcls\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mload_image\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfn\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mmerge\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcls\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_open_args\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 126\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 127\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mshow\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mctx\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
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+
"\u001b[0;32m/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/fastai/vision/core.py\u001b[0m in \u001b[0;36mload_image\u001b[0;34m(fn, mode)\u001b[0m\n\u001b[1;32m 96\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mload_image\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfn\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmode\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 97\u001b[0m \u001b[0;34m\"Open and load a `PIL.Image` and convert to `mode`\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 98\u001b[0;31m \u001b[0mim\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mImage\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mopen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfn\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 99\u001b[0m \u001b[0mim\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mload\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 100\u001b[0m \u001b[0mim\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mim\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_new\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mim\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mim\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
|
380 |
+
"\u001b[0;32m/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/PIL/Image.py\u001b[0m in \u001b[0;36mopen\u001b[0;34m(fp, mode, formats)\u001b[0m\n\u001b[1;32m 3234\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3235\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mfilename\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 3236\u001b[0;31m \u001b[0mfp\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mbuiltins\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mopen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfilename\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m\"rb\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 3237\u001b[0m \u001b[0mexclusive_fp\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mTrue\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3238\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
|
381 |
+
"\u001b[0;31mFileNotFoundError\u001b[0m: [Errno 2] No such file or directory: 'Benign1.jpg'"
|
382 |
+
]
|
383 |
+
}
|
384 |
+
],
|
385 |
+
"source": [
|
386 |
+
" # im = PILImage.create('Benign1.jpg')\n",
|
387 |
+
" # im.thumbnail((192,192))\n"
|
388 |
+
]
|
389 |
+
},
|
390 |
+
{
|
391 |
+
"cell_type": "code",
|
392 |
+
"execution_count": null,
|
393 |
+
"metadata": {},
|
394 |
+
"outputs": [
|
395 |
+
{
|
396 |
+
"ename": "NotImplementedError",
|
397 |
+
"evalue": "cannot instantiate 'WindowsPath' on your system",
|
398 |
+
"output_type": "error",
|
399 |
+
"traceback": [
|
400 |
+
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
401 |
+
"\u001b[0;31mNotImplementedError\u001b[0m Traceback (most recent call last)",
|
402 |
+
"\u001b[0;32m/var/folders/gm/h3z3dxv12z73tt5_q7j7kc6h0000gn/T/ipykernel_97601/243768304.py\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mlearn\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mload_learner\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'export.pkl'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
|
403 |
+
"\u001b[0;32m/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/fastai/learner.py\u001b[0m in \u001b[0;36mload_learner\u001b[0;34m(fname, cpu, pickle_module)\u001b[0m\n\u001b[1;32m 444\u001b[0m \u001b[0mdistrib_barrier\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 445\u001b[0m \u001b[0mmap_loc\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m'cpu'\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mcpu\u001b[0m \u001b[0;32melse\u001b[0m \u001b[0mdefault_device\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 446\u001b[0;31m \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mres\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mtorch\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mload\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfname\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmap_location\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mmap_loc\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mpickle_module\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mpickle_module\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 447\u001b[0m \u001b[0;32mexcept\u001b[0m \u001b[0mAttributeError\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0me\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 448\u001b[0m \u001b[0me\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0margs\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0;34mf\"Custom classes or functions exported with your `Learner` not available in namespace.\\Re-declare/import before loading:\\n\\t{e.args[0]}\"\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
|
404 |
+
"\u001b[0;32m/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/torch/serialization.py\u001b[0m in \u001b[0;36mload\u001b[0;34m(f, map_location, pickle_module, weights_only, **pickle_load_args)\u001b[0m\n\u001b[1;32m 787\u001b[0m \u001b[0;32mexcept\u001b[0m \u001b[0mRuntimeError\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0me\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 788\u001b[0m \u001b[0;32mraise\u001b[0m \u001b[0mpickle\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mUnpicklingError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mUNSAFE_MESSAGE\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0mstr\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0me\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mfrom\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 789\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0m_load\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mopened_zipfile\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmap_location\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mpickle_module\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mpickle_load_args\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 790\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mweights_only\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 791\u001b[0m \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
|
405 |
+
"\u001b[0;32m/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/torch/serialization.py\u001b[0m in \u001b[0;36m_load\u001b[0;34m(zip_file, map_location, pickle_module, pickle_file, **pickle_load_args)\u001b[0m\n\u001b[1;32m 1129\u001b[0m \u001b[0munpickler\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mUnpicklerWrapper\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdata_file\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mpickle_load_args\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1130\u001b[0m \u001b[0munpickler\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpersistent_load\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mpersistent_load\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1131\u001b[0;31m \u001b[0mresult\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0munpickler\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mload\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1132\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1133\u001b[0m \u001b[0mtorch\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_utils\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_validate_loaded_sparse_tensors\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
|
406 |
+
"\u001b[0;32m/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/pathlib.py\u001b[0m in \u001b[0;36m__new__\u001b[0;34m(cls, *args, **kwargs)\u001b[0m\n\u001b[1;32m 1023\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_flavour\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mis_supported\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1024\u001b[0m raise NotImplementedError(\"cannot instantiate %r on your system\"\n\u001b[0;32m-> 1025\u001b[0;31m % (cls.__name__,))\n\u001b[0m\u001b[1;32m 1026\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_init\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1027\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
|
407 |
+
"\u001b[0;31mNotImplementedError\u001b[0m: cannot instantiate 'WindowsPath' on your system"
|
408 |
+
]
|
409 |
+
}
|
410 |
+
],
|
411 |
+
"source": [
|
412 |
+
"learn = load_learner('export.pkl')"
|
413 |
+
]
|
414 |
+
},
|
415 |
+
{
|
416 |
+
"cell_type": "code",
|
417 |
+
"execution_count": null,
|
418 |
+
"metadata": {},
|
419 |
+
"outputs": [
|
420 |
+
{
|
421 |
+
"data": {
|
422 |
+
"text/plain": [
|
423 |
+
"('benign', tensor(0), tensor([0.8787, 0.1213]))"
|
424 |
+
]
|
425 |
+
},
|
426 |
+
"execution_count": 6,
|
427 |
+
"metadata": {},
|
428 |
+
"output_type": "execute_result"
|
429 |
+
}
|
430 |
+
],
|
431 |
+
"source": [
|
432 |
+
"learn.predict(im)"
|
433 |
+
]
|
434 |
+
},
|
435 |
+
{
|
436 |
+
"cell_type": "code",
|
437 |
+
"execution_count": null,
|
438 |
+
"metadata": {},
|
439 |
+
"outputs": [],
|
440 |
+
"source": [
|
441 |
+
"categories = ('Benign', 'Malignant')\n",
|
442 |
+
"\n",
|
443 |
+
"def classify_image(img):\n",
|
444 |
+
" pred,idx,probs = learn.predict(img)\n",
|
445 |
+
" return dict(zip(categories, map(float,probs)))"
|
446 |
+
]
|
447 |
+
},
|
448 |
+
{
|
449 |
+
"cell_type": "code",
|
450 |
+
"execution_count": null,
|
451 |
+
"metadata": {},
|
452 |
+
"outputs": [
|
453 |
+
{
|
454 |
+
"data": {
|
455 |
+
"text/plain": [
|
456 |
+
"{'Benign': 0.8787491321563721, 'Malignant': 0.12125089019536972}"
|
457 |
+
]
|
458 |
+
},
|
459 |
+
"execution_count": 8,
|
460 |
+
"metadata": {},
|
461 |
+
"output_type": "execute_result"
|
462 |
+
}
|
463 |
+
],
|
464 |
+
"source": [
|
465 |
+
"classify_image(im)"
|
466 |
+
]
|
467 |
+
},
|
468 |
+
{
|
469 |
+
"cell_type": "code",
|
470 |
+
"execution_count": null,
|
471 |
+
"metadata": {},
|
472 |
+
"outputs": [
|
473 |
+
{
|
474 |
+
"name": "stderr",
|
475 |
+
"output_type": "stream",
|
476 |
+
"text": [
|
477 |
+
"c:\\Users\\ntram\\Anaconda3\\lib\\site-packages\\gradio\\inputs.py:259: UserWarning: Usage of gradio.inputs is deprecated, and will not be supported in the future, please import your component from gradio.components\n",
|
478 |
+
" warnings.warn(\n",
|
479 |
+
"c:\\Users\\ntram\\Anaconda3\\lib\\site-packages\\gradio\\inputs.py:262: UserWarning: `optional` parameter is deprecated, and it has no effect\n",
|
480 |
+
" super().__init__(\n",
|
481 |
+
"c:\\Users\\ntram\\Anaconda3\\lib\\site-packages\\gradio\\outputs.py:197: UserWarning: Usage of gradio.outputs is deprecated, and will not be supported in the future, please import your components from gradio.components\n",
|
482 |
+
" warnings.warn(\n",
|
483 |
+
"c:\\Users\\ntram\\Anaconda3\\lib\\site-packages\\gradio\\outputs.py:200: UserWarning: The 'type' parameter has been deprecated. Use the Number component instead.\n",
|
484 |
+
" super().__init__(num_top_classes=num_top_classes, type=type, label=label)\n"
|
485 |
+
]
|
486 |
+
},
|
487 |
+
{
|
488 |
+
"name": "stdout",
|
489 |
+
"output_type": "stream",
|
490 |
+
"text": [
|
491 |
+
"Running on local URL: http://127.0.0.1:7860\n",
|
492 |
+
"\n",
|
493 |
+
"To create a public link, set `share=True` in `launch()`.\n"
|
494 |
+
]
|
495 |
+
},
|
496 |
+
{
|
497 |
+
"data": {
|
498 |
+
"text/plain": []
|
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+
},
|
500 |
+
"execution_count": 9,
|
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+
"metadata": {},
|
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"output_type": "execute_result"
|
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+
},
|
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+
{
|
505 |
+
"data": {
|
506 |
+
"text/html": [
|
507 |
+
"\n",
|
508 |
+
"<style>\n",
|
509 |
+
" /* Turns off some styling */\n",
|
510 |
+
" progress {\n",
|
511 |
+
" /* gets rid of default border in Firefox and Opera. */\n",
|
512 |
+
" border: none;\n",
|
513 |
+
" /* Needs to be in here for Safari polyfill so background images work as expected. */\n",
|
514 |
+
" background-size: auto;\n",
|
515 |
+
" }\n",
|
516 |
+
" progress:not([value]), progress:not([value])::-webkit-progress-bar {\n",
|
517 |
+
" background: repeating-linear-gradient(45deg, #7e7e7e, #7e7e7e 10px, #5c5c5c 10px, #5c5c5c 20px);\n",
|
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+
" }\n",
|
519 |
+
" .progress-bar-interrupted, .progress-bar-interrupted::-webkit-progress-bar {\n",
|
520 |
+
" background: #F44336;\n",
|
521 |
+
" }\n",
|
522 |
+
"</style>\n"
|
523 |
+
],
|
524 |
+
"text/plain": [
|
525 |
+
"<IPython.core.display.HTML object>"
|
526 |
+
]
|
527 |
+
},
|
528 |
+
"metadata": {},
|
529 |
+
"output_type": "display_data"
|
530 |
+
},
|
531 |
+
{
|
532 |
+
"data": {
|
533 |
+
"text/html": [
|
534 |
+
"\n",
|
535 |
+
"<style>\n",
|
536 |
+
" /* Turns off some styling */\n",
|
537 |
+
" progress {\n",
|
538 |
+
" /* gets rid of default border in Firefox and Opera. */\n",
|
539 |
+
" border: none;\n",
|
540 |
+
" /* Needs to be in here for Safari polyfill so background images work as expected. */\n",
|
541 |
+
" background-size: auto;\n",
|
542 |
+
" }\n",
|
543 |
+
" progress:not([value]), progress:not([value])::-webkit-progress-bar {\n",
|
544 |
+
" background: repeating-linear-gradient(45deg, #7e7e7e, #7e7e7e 10px, #5c5c5c 10px, #5c5c5c 20px);\n",
|
545 |
+
" }\n",
|
546 |
+
" .progress-bar-interrupted, .progress-bar-interrupted::-webkit-progress-bar {\n",
|
547 |
+
" background: #F44336;\n",
|
548 |
+
" }\n",
|
549 |
+
"</style>\n"
|
550 |
+
],
|
551 |
+
"text/plain": [
|
552 |
+
"<IPython.core.display.HTML object>"
|
553 |
+
]
|
554 |
+
},
|
555 |
+
"metadata": {},
|
556 |
+
"output_type": "display_data"
|
557 |
+
},
|
558 |
+
{
|
559 |
+
"data": {
|
560 |
+
"text/html": [
|
561 |
+
"\n",
|
562 |
+
"<style>\n",
|
563 |
+
" /* Turns off some styling */\n",
|
564 |
+
" progress {\n",
|
565 |
+
" /* gets rid of default border in Firefox and Opera. */\n",
|
566 |
+
" border: none;\n",
|
567 |
+
" /* Needs to be in here for Safari polyfill so background images work as expected. */\n",
|
568 |
+
" background-size: auto;\n",
|
569 |
+
" }\n",
|
570 |
+
" progress:not([value]), progress:not([value])::-webkit-progress-bar {\n",
|
571 |
+
" background: repeating-linear-gradient(45deg, #7e7e7e, #7e7e7e 10px, #5c5c5c 10px, #5c5c5c 20px);\n",
|
572 |
+
" }\n",
|
573 |
+
" .progress-bar-interrupted, .progress-bar-interrupted::-webkit-progress-bar {\n",
|
574 |
+
" background: #F44336;\n",
|
575 |
+
" }\n",
|
576 |
+
"</style>\n"
|
577 |
+
],
|
578 |
+
"text/plain": [
|
579 |
+
"<IPython.core.display.HTML object>"
|
580 |
+
]
|
581 |
+
},
|
582 |
+
"metadata": {},
|
583 |
+
"output_type": "display_data"
|
584 |
+
},
|
585 |
+
{
|
586 |
+
"data": {
|
587 |
+
"text/html": [
|
588 |
+
"\n",
|
589 |
+
" <div>\n",
|
590 |
+
" <progress value='0' class='' max='1' style='width:300px; height:20px; vertical-align: middle;'></progress>\n",
|
591 |
+
" \n",
|
592 |
+
" </div>\n",
|
593 |
+
" "
|
594 |
+
],
|
595 |
+
"text/plain": [
|
596 |
+
"<IPython.core.display.HTML object>"
|
597 |
+
]
|
598 |
+
},
|
599 |
+
"metadata": {},
|
600 |
+
"output_type": "display_data"
|
601 |
+
},
|
602 |
+
{
|
603 |
+
"data": {
|
604 |
+
"text/html": [
|
605 |
+
"\n",
|
606 |
+
"<style>\n",
|
607 |
+
" /* Turns off some styling */\n",
|
608 |
+
" progress {\n",
|
609 |
+
" /* gets rid of default border in Firefox and Opera. */\n",
|
610 |
+
" border: none;\n",
|
611 |
+
" /* Needs to be in here for Safari polyfill so background images work as expected. */\n",
|
612 |
+
" background-size: auto;\n",
|
613 |
+
" }\n",
|
614 |
+
" progress:not([value]), progress:not([value])::-webkit-progress-bar {\n",
|
615 |
+
" background: repeating-linear-gradient(45deg, #7e7e7e, #7e7e7e 10px, #5c5c5c 10px, #5c5c5c 20px);\n",
|
616 |
+
" }\n",
|
617 |
+
" .progress-bar-interrupted, .progress-bar-interrupted::-webkit-progress-bar {\n",
|
618 |
+
" background: #F44336;\n",
|
619 |
+
" }\n",
|
620 |
+
"</style>\n"
|
621 |
+
],
|
622 |
+
"text/plain": [
|
623 |
+
"<IPython.core.display.HTML object>"
|
624 |
+
]
|
625 |
+
},
|
626 |
+
"metadata": {},
|
627 |
+
"output_type": "display_data"
|
628 |
+
},
|
629 |
+
{
|
630 |
+
"data": {
|
631 |
+
"text/html": [
|
632 |
+
"\n",
|
633 |
+
" <div>\n",
|
634 |
+
" <progress value='0' class='' max='1' style='width:300px; height:20px; vertical-align: middle;'></progress>\n",
|
635 |
+
" \n",
|
636 |
+
" </div>\n",
|
637 |
+
" "
|
638 |
+
],
|
639 |
+
"text/plain": [
|
640 |
+
"<IPython.core.display.HTML object>"
|
641 |
+
]
|
642 |
+
},
|
643 |
+
"metadata": {},
|
644 |
+
"output_type": "display_data"
|
645 |
+
}
|
646 |
+
],
|
647 |
+
"source": [
|
648 |
+
"image = gr.inputs.Image(shape=(192,192))\n",
|
649 |
+
"label = gr.outputs.Label()\n",
|
650 |
+
"examples = ['Benign1.jpg','Benign2.jpg','Benign3.jpg', 'Malignant1.jpg', 'Malignant2.jpg', 'Malignant3.jpg']\n",
|
651 |
+
"\n",
|
652 |
+
"intf = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples)\n",
|
653 |
+
"intf.launch(inline=False)"
|
654 |
+
]
|
655 |
+
},
|
656 |
+
{
|
657 |
+
"cell_type": "code",
|
658 |
+
"execution_count": null,
|
659 |
+
"metadata": {},
|
660 |
+
"outputs": [],
|
661 |
+
"source": []
|
662 |
+
}
|
663 |
+
],
|
664 |
+
"metadata": {
|
665 |
+
"kernelspec": {
|
666 |
+
"display_name": "base",
|
667 |
+
"language": "python",
|
668 |
+
"name": "python3"
|
669 |
+
},
|
670 |
+
"language_info": {
|
671 |
+
"codemirror_mode": {
|
672 |
+
"name": "ipython",
|
673 |
+
"version": 3
|
674 |
+
},
|
675 |
+
"file_extension": ".py",
|
676 |
+
"mimetype": "text/x-python",
|
677 |
+
"name": "python",
|
678 |
+
"nbconvert_exporter": "python",
|
679 |
+
"pygments_lexer": "ipython3",
|
680 |
+
"version": "3.7.6"
|
681 |
+
},
|
682 |
+
"orig_nbformat": 4
|
683 |
+
},
|
684 |
+
"nbformat": 4,
|
685 |
+
"nbformat_minor": 2
|
686 |
+
}
|
app.py
ADDED
@@ -0,0 +1,19 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
from fastai.vision.all import *
|
2 |
+
import gradio as gr
|
3 |
+
learn = load_learner('export.pkl')
|
4 |
+
|
5 |
+
categories = ('Benign', 'Malignant')
|
6 |
+
|
7 |
+
|
8 |
+
def classify_image(img):
|
9 |
+
pred,idx,probs = learn.predict(img)
|
10 |
+
return dict(zip(categories, map(float,probs)))
|
11 |
+
|
12 |
+
image = gr.inputs.Image(shape=(192,192))
|
13 |
+
label = gr.outputs.Label()
|
14 |
+
examples = ['Benign 1.jpg','Benign 2.jpg','Benign 3.jpg', 'Malignant 1.jpg',
|
15 |
+
'Malignant 2.jpg', 'Malignant 3.jpg']
|
16 |
+
|
17 |
+
intf = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples)
|
18 |
+
intf.launch(inline=False)
|
19 |
+
|
export.pkl
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:df104c05b8c1043f4120501d5ad99bc4c7e082464d48db3038b54aff5064c0cc
|
3 |
+
size 114811675
|
requirements.txt
ADDED
@@ -0,0 +1,2 @@
|
|
|
|
|
|
|
1 |
+
fastai
|
2 |
+
timm
|